Intelligent Analytics With Advanced Multi Industry Applications

Many fundamental technological and managerial issues surrounding the development and implementation of intelligent analytics within multi-industry applications remain unsolved. There are still questions surrounding the foundation of intelligent analytics, the elements, the big characteristics, and the effects on business, management, technology, and society. Research is devoted to answering these questions and understanding how intelligent analytics can improve healthcare, mobile commerce, web services, cloud services, blockchain, 5G development, digital transformation, and more. Intelligent Analytics With Advanced Multi-Industry Applications is a critical reference source that explores cutting-edge theories, technologies, and methodologies of intelligent analytics with multi-industry applications and emphasizes the integration of artificial intelligence, business intelligence, big data, and analytics from a perspective of computing, service, and management. This book also provides real-world applications of the proposed concept of intelligent analytics to e-SMACS (electronic, social, mobile, analytics, cloud, and service) commerce and services, healthcare, the internet of things, the sharing economy, cloud computing, blockchain, and Industry 4.0. This book is ideal for scientists, engineers, educators, university students, service and management professionals, policymakers, decision makers, practitioners, stakeholders, researchers, and others who have an interest in how intelligent analytics are being implemented and utilized in diverse industries.

Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.

1. Covers latest concepts in intelligent analytics for industry 4.0. 2. Presents the applications of intelligent analytics for various industry 4.0 domains. 3. Covers latest research topics in the field. 4. Written in a comprehensive and simple manner. 5. The text is accompanied by tables and illustrative figures for better understanding of the topic.

Socioeconomic development has drawn increasing attention in academia, industries, and governments. The relationship between big data and its technologies and socioeconomic development has drawn certain attention in academia. Socioeconomic development depends not only on big data, but also on big data technologies. However, the relationship between big data and socioeconomic development is not adequately covered in current research. The Handbook of Research on Driving Socioeconomic Development With Big Data provides an original and innovative understanding of and insight into how the proposed theories, technologies, and methodologies of big data can improve socioeconomic development and sustainable development in terms of business and services, healthcare, the internet of everything, sharing economy, and more. Covering topics such as corporate social responsibility, management applications, and process mining, this major reference work is an excellent resource for data scientists, business leaders and executives, IT professionals, government officials, economists, sociologists, librarians, students, researchers, and academicians.

Computers and machines were developed to reduce time consumption and manual human efforts to complete projects efficiently. With fast-growing technologies in the field, we have finally reached a stage where almost everyone in the world has access to these high technologies. However, this is just a starting phase because future development is taking a more advanced route in the shape of artificial intelligence (AI). Although AI is under the computer science umbrella, nowadays there is no field unaffected by this high technology. The overall aim of using intelligence learning methods is to train machines to think intelligently and make decisions in different situations the same as humans. Previously, machines were doing what they were programmed to do, but now with AI, devices can think and behave like a human being. This book aims to present the application of advanced analytics and AI in different industries as practical tools to develop prediction, optimization, and make decision models.

In the age of transformative artificial intelligence (AI), which has the potential to revolutionize our lives, this book provides a comprehensive exploration of successful research and applications in AI and data analytics. Covering innovative approaches, advanced algorithms, and data analysis methodologies, this book addresses complex problems across topics such as machine learning, pattern recognition, data mining, optimization, and predictive modeling. With clear explanations, practical examples, and cutting-edge research, this book seeks to expand the understanding of a wide readership, including students, researchers, practitioners, and technology enthusiasts eager to explore these exciting fields. Featuring real-world applications in education, health care, climate modeling, cybersecurity, smart transportation, conversational systems, and material analysis, among others, this book highlights how these technologies can drive innovation and generate competitive advantages.

The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers. Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies.

Blockchain technology presents numerous advantages that include increased transparency, reduced transaction costs, faster transaction settlement, automation of information, increased traceability, improved customer experience, improved digital identity, better cyber security, and user-controlled networks. These potential applications are widespread and diverse including funds transfer, smart contracts, e-voting, efficient supply chain, and more in nearly every sector of society including finance, healthcare, law, trade, real estate, and other important areas. However, there are challenges and limitations that exist such as high energy consumption, limited scalability, complexity, security, network size, lack of regulations, and other critical issues. Nevertheless, blockchain is an attractive technology and has much to offer to the modern-day industry. Industry Use Cases on Blockchain Technology Applications in IoT and the Financial Sector investigates blockchain technology’s adoption and effectiveness in multiple industries and for the internet of things (IoT)-based applications, presents use cases from industrial and financial sectors as well as from other transaction-based services, and fills a gap in this respect by extending the existing body of knowledge in the suggested field. While highlighting topics such as cybersecurity, use cases, and models for blockchain implementation, this book is ideal for business managers, financial accountants, practitioners, researchers, academicians, and students interested in blockchain technology’s role and implementation in IoT and the financial sector.